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R U :-) or :-( ? Character- vs. Word-Gram Feature Selection for Sentiment Classification of OSN Corpora / Ben Blamey; Tom Crick; Giles Oatley

Research and Development in Intelligent Systems XXIX, Pages: 207 - 212

Swansea University Author: Crick, Tom

DOI (Published version): 10.1007/978-1-4471-4739-8_16

Abstract

Binary sentiment classification, or sentiment analysis, is the task of computing the sentiment of a document, i.e. whether it contains broadly positive or negative opinions. The topic is well-studied, and the intuitive approach of using words as classification features is the basis of most technique...

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Published in: Research and Development in Intelligent Systems XXIX
ISBN: 978-1-4471-4738-1 978-1-4471-4739-8
Published: Cambridge, UK Springer 2012
Online Access: https://link.springer.com/chapter/10.1007%2F978-1-4471-4739-8_16
URI: https://cronfa.swan.ac.uk/Record/cronfa43404
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Abstract: Binary sentiment classification, or sentiment analysis, is the task of computing the sentiment of a document, i.e. whether it contains broadly positive or negative opinions. The topic is well-studied, and the intuitive approach of using words as classification features is the basis of most techniques documented in the literature. The alternative character n-gram language model has been applied successfully to a range of NLP tasks, but its effectiveness at sentiment classification seems to be under-investigated, and results are mixed. We present an investigation of the application of the character n-gram model to text classification of corpora from online social networks, the first such documented study, where text is known to be rich in so-called unnatural language, also introducing a novel corpus of Facebook photo comments. Despite hoping that the flexibility of the character n-gram approach would be well-suited to unnatural language phenomenon, we find little improvement over the baseline algorithms employing the word n-gram language model.
Item Description: 32nd SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence (AI-2012)
College: College of Science
Start Page: 207
End Page: 212